The huge volume of image and video data available on the networks (e.g., the Internet), scientific databases, and newspaper archives, along with recent advances in efficient (approximate) image matching schemes have opened the door for a number of large scale matching applications. The general field of content based image retrieval (CBIR) uses many different input modalities to search for similar images in a database.
In the realm of freeform hand sketches using interactive displays and a standard drawing interface, if a novice user is asked to sketch a face, the result will typically look rough and unrefined. Similarly, if asked to draw a bicycle, for example, most of users would have a difficult time depicting how the frame and wheels relate to each other.
One solution is to search for an image of the object to be drawn, and to either trace the object or use the object in some other way, such as for a reference. However, aside from the difficulty of finding an image of what is to be drawn, simply tracing object edges eliminates much of the essence of drawing (there is very little freedom in tracing strokes). Conversely, drawing on blank paper with only the image in the mind's eye gives the drawer more freedom. Without significant training it is difficult to get the relative proportions of objects correct. Thus, freehand drawing remains a frustrating endeavor.